Paper Info
Title
Multi-Objective Optimisation Of Multi-Task Scheduling In Cloud Manufacturing
Abstract
Cloud manufacturing is a consumer-centric requirement-driven manufacturing paradigm that integrates distributed resources for providing services to consumers in an on-demand manner. Scheduling of multiple tasks is an important technical means for satisfying consumer requirements in cloud manufacturing. However, high individualised requirements and the associated complex task structures complicate the task scheduling in cloud manufacturing. This paper establishes a more comprehensive model for scheduling multiple distinct tasks with complicated manufacturing processes. The hierarchical relationships (a mixture of dependency and independency) of subtasks within tasks are considered. The objectives involve three kinds of time and cost factors, namely processing time, setup time, transfer time and the respective cost. In addition, service quality is also considered into the optimisation objective. Two multi-objective-meta-heuristic algorithms, i.e. ACO-based multi-objective algorithm (MACO) and NSGA-II-based multi-objective algorithm (MGA), are designed to solve the scheduling problem. A detailed analysis of the performance of the two algorithms is performed by applying them to several different scheduling instances. Experimental results indicate that in most cases the MACO algorithm can obtain a more diverse set of Pareto solutions hence offering more alternatives to meet widely different users' needs.
Year
DOI
Venue
2019
10.1080/00207543.2018.1538579
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Keywords
DocType
Volume
Multi-task scheduling, multi-objective optimisation, Pareto set, meta-heuristic, cloud manufacturing
Journal
57
Issue
ISSN
Citations 
12
0020-7543
3
PageRank 
References 
Authors
0.39
16
4
Name
Order
Citations
PageRank
Feng Li1113.23
Lin Zhang214616.93
T. W. Liao31195.30
Yongkui Liu421014.54